OutSee, a genomics and drug discovery company pioneering a unique AI-based predictive genomics approach to target discovery, announced it has secured £1.8 million in seed funding, led by Ahren Innovation Capital and with additional investment from Kadmos Capital, Empirical Ventures, and Panacea Ventures.
PhotonDelta, the Netherlands-based photonic chip accelerator, and Luminate NY, the accelerator for startups with optics, photonics, and imaging enabled technologies, have entered into a strategic collaboration to support the growth of early-stage photonics companies across North America and the Netherlands.
A £400,000 project led by the Centre for Business and Industry Transformation (CBIT) at Nottingham Business School aims to bridge the gap between academic research and industry by training technology transfer professionals and STEM researchers in entrepreneurship – with a focus on AI to empower businesses.
The iconic Mandarin Oriental Hyde Park, London has installed solar heat technology from Naked Energy on its rooftop. This installation makes the luxury hotel the first in the UK to use Naked Energy’s solar thermal collectors, demonstrating its commitment to reducing carbon emissions and energy consumption.
Tadaweb has secured $20 million to scale its Small Data Operating System for publicly available information (PAI) and open-source intelligence (OSINT). The software-as-a-service (SaaS) platform is used by defence, national security, public safety, cyber threat intelligence, and corporate security organisations across Europe and the US to boost the efficiency of analysts and investigators by reducing time to insight from days to minutes.
As the saying goes, ‘there’s no need to reinvent the wheel’. If there’s a product or service on the market that already does its job well enough, then launching a competing solution might see you enjoy some success – particularly if you can improve or tweak it enough that you attract clients to your business rather than others.
Controversies over data, intellectual property, and licensing go hand in hand with generative AI (GenAI). The machine learning algorithms used by GenAI models require data to identify patterns and interdependencies that enable them to generate suitable responses to prompts. Therefore, volume and data quality are fundamentally important to the effectiveness of AI models.












